Combinatorial CRISPR/Cas9 Screening Reveals Epistatic Networks of Interacting Tumor Suppressor Genes and Therapeutic

Xiaoyu Zhao1,2, Jinyu Li1, Zhimin Liu2,3,4,5

  • 1Department of Pathology and Cancer Center, Renaissance School of Medicine, Stony Brook, New York.

Cancer Research
|September 25, 2021
PubMed

Insights

Understanding how multiple genetic changes drive cancer is key. This study reveals that cooperating tumor suppressor genes (TSGs) in breast cancer often share functions and exhibit transcriptional epistasis, impacting therapeutic targets and patient tumors.

Area of Science:

  • Oncology
  • Genetics
  • Molecular Biology

Background:

  • Most cancers involve multiple genetic alterations, but their collaborative roles in tumor development are poorly understood.
  • Investigating genetic interactions among tumor suppressor genes (TSGs) is crucial for deciphering complex tumorigenesis.

Purpose of the Study:

  • To elucidate the mechanistic insights into tumor-promoting genetic interactions among TSGs.
  • To identify how combinatorial TSG alterations collaborate during cancer development.

Main Methods:

  • Utilized combinatorial CRISPR screening in human mammary epithelial cells.
  • Integrated single-cell transcriptomic profiling to analyze gene interactions and transcriptional changes.
  • Performed genetic interaction profiling to map TSG networks.

Main Results:

  • Identified TSG interaction networks forming "cliques" where genes within a set cooperate oncogenically.
  • Demonstrated that cooperating TSGs predominantly share overlapping functions.
  • Observed transcriptional epistasis in cooperating TSGs that synergize tumorigenesis, affecting key mediators like CDK4, SRPK1, and DNMT1.
  • Validated epistatic alterations in human breast cancer patient tumors, with an estimated 50% of differentially expressed genes influenced by these interactions.

Conclusions:

  • Transcriptional epistasis is a central mechanism in multigenic breast cancer progression.
  • Cooperating TSGs exhibit functional overlap and drive cancer through synergistic transcriptional effects.
  • This study provides a framework for developing therapeutic strategies targeting multiple driver gene interactions in cancer.

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